Release Train Engineer

Mastek
London
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineer

Data Engineer

Environmental Data Analyst Apprentice

Machine Learning Engineer

Data Engineer (Automation)

Job Title: Release Train Engineer

Location: London, UK (3 days a week in office)

SC Cleared: Required

Job Type: Full-Time

Experience: 8+ years

Job Overview:


We are seeking a highly motivated and experienced Release Train Engineer (RTE) to facilitate the successful delivery of our cutting-edge Azure Databricks platform for economic data. This platform is critical to our Monetary Analysis, Forecasting, and Modelling capabilities. The RTE will serve as a servant leader and coach for multiple Agile teams, ensuring alignment with programme objectives, removing impediments, and driving continuous improvement within the Agile Release Train (ART). This role demands a strong understanding of Agile principles, excellent communication and facilitation skills, and a passion for fostering a collaborative and high-performing team environment.


Responsibilities:

  • ART Facilitation:
  • Facilitate ART events, including Programme Increment (PI) Planning, Scrum of Scrums, System Demos, and Inspect & Adapt workshops.
  • Drive the cadence and synchronisation of ART activities, ensuring alignment with the overall programme roadmap.
  • Coach teams and stakeholders on Agile principles and practices, promoting a culture of continuous learning and improvement.
  • Impediment Removal:
  • Identify and escalate impediments that block the progress of the ART and individual teams.
  • Work with stakeholders to resolve dependencies, manage risks, and mitigate issues proactively.
  • Facilitate cross-team communication and collaboration to ensure smooth workflow.
  • PI Planning:
  • Lead the preparation and execution of PI Planning events, ensuring clear objectives, well-defined features, and realistic commitments.
  • Facilitate the development of PI Objectives and ensure alignment with strategic themes.
  • Track progress against PI Objectives and report on key metrics.
  • Continuous Improvement:
  • Promote a culture of continuous improvement within the ART by facilitating retrospectives and implementing agreed-upon actions.
  • Identify and implement process improvements to enhance efficiency and effectiveness.
  • Champion the adoption of Agile best practices and principles.
  • Stakeholder Management:
  • Build strong relationships with stakeholders at all levels, including business owners, product managers, and technical teams.
  • Communicate ART progress, risks, and dependencies effectively.
  • Manage stakeholder expectations and ensure alignment on priorities.
  • Metrics and Reporting:
  • Collect and analyse key metrics to track ART performance and identify areas for improvement.
  • Provide regular reports on ART progress to stakeholders.
  • Use data to drive decision-making and continuous improvement.
  • Collaboration with System Architect/Engineering:
  • Work closely with the System Architect/Engineering to support the architectural runway and ensure technical alignment within the ART.


Skills & Experience:

  • 5+ years of experience working in an Agile environment, with at least 3+ years in a Release Train Engineer or similar leadership role.
  • Deep understanding of Agile principles, practices, and frameworks (e.g., Scrum, Kanban, SAFe).
  • Proven experience facilitating large-scale Agile events, such as PI Planning.
  • Excellent communication, interpersonal, and facilitation skills.
  • Strong problem-solving and conflict-resolution skills.
  • Ability to influence and motivate teams without direct authority.
  • Experience working with distributed teams.
  • Familiarity with Jira or similar Agile project management tools.
  • Experience in a data-driven environment is highly desirable.
  • Experience with Azure Databricks or similar big data platforms is a plus.
  • Desirable Skills & Experience:
  • SAFe Program Consultant (SPC) or SAFe RTE certification.
  • Experience working with economic data or in the financial services industry.
  • Knowledge of DevOps practices and principles.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Careers

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

Jobs

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

Careers Jobs

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.